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Network dynamics in the healthy and epileptic developing brain

Rosch, RE; Baldeweg, T; Moeller, F; Baier, G; (2017) Network dynamics in the healthy and epileptic developing brain. Network Neuroscience 10.1162/NETN_a_00026. (In press). Green open access

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Abstract

Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarised along different dimensions using network-level quantitative measures, e.g. channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different time scales and can be tracked dynamically. Here we describe the dynamics of network-state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n=8, age: 1-8 months). We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity. We further show that EEGs from different patient groups and controls may be distinguishable based on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups. These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in future inform the clinical use of quantitative EEG for diagnosis.

Type: Article
Title: Network dynamics in the healthy and epileptic developing brain
Open access status: An open access version is available from UCL Discovery
DOI: 10.1162/NETN_a_00026
Publisher version: http://dx.doi.org/10.1162/NETN_a_00026
Language: English
Additional information: Copyright © 2017 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: EEG, Dynamic Network, Epilepsy, State Transitions, Computational Analysis
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > UCL GOS Institute of Child Health > ICH Developmental Neurosciences Prog
URI: http://discovery.ucl.ac.uk/id/eprint/1576370
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